While mail systems have always strived for accuracy and integrity to ensure that letters arrive at their proper destination in good order and in a timely manner, integrity verification is of paramount importance in the industry today. Issues such as inspecting sequential page numbering, inspecting correct postage, and ensuring contents to wrapper matching now need to be performed in a highly accurate and efficient manner.
Early prior art methods of managing the integrity of a large volume mailing typically required the use of legions of employees manually verifying the accuracy of work pieces before they were sent out. While these methods were adequate for their time, contemporary requirements for enormous and time-critical mailings have led to the development of high-speed feeder systems with a capacity to handle enormous quantities of output. These high capacity feeders now require only a minimum of human involvement, leaving those early quality control methods inherently obsolescent.
Attempts at integrity verification for contemporary feeder systems have involved the placement of marks directly upon the work piece that encode basic information about the work piece that can be read by a somewhat rudimentary machine vision system to glean information about the status of the process. One such mark is the Optical Mark Recognition (OMR). OMR marks can be read by a light probe to gain information about a particular work piece for use in integrity verification such as sequential numbering or ensuring all pages are collated together into a single mailing. The problem with the OMR technique is that it provides only limited information and requires the disfigurement of the work piece itself for the sole purpose of integrity verification, a process which when completed leaves the markings remaining permanently on the work piece. This is undesirable in the industry, which would prefer that only information pertaining to the document's original purpose be present upon receipt by the recipient.
Later developments use the now ubiquitous bar-coding method. While providing more detailed information that can be useful in integrity verification techniques, as with OMR this too disfigures the work piece for peripheral purposes, and provides the additional disadvantage of tending to make the recipient feel like “just a number”.
More recent techniques have involved the use of area-scanning cameras that capture images in a manner not unlike a common consumer digital camera. These cameras are used to scan an area of a document, with Optical Character Recognition (OCR) techniques subsequently performed to glean information from the scanned region of the work piece. This provides the advantage of limiting the disfigurement of the work piece by attempting to use existing information such as the address label to verify the accuracy of the mail out. The problem with this technique is that area-scanning cameras are incapable of scanning a large area image in a rapid manner, and require waiting for the entire area to be scanned before the image can be processed for information.
A further problem in the field is with the capturing of embossed or three dimensional characters on a work piece, such as a credit card. Imaging or reading the embossed characters has proved to be inherently difficult. Since feeder systems are frequently employed to mail out new and renewed credit cards, a need exists to capture the printed information on those cards to ensure the integrity of the mail out. Prior art systems will typically employ a ring light, also used with other applications, to properly illuminate the characters for improved contrast. However, if the ring light is not precisely positioned directly on top of the target, which occurs with regularity, a reader will be unable to properly capture the information due to shadowing and other problems.
One method around this problem has been to try to read matching information on a magnetic stripe that often accompanies these cards. However, not all cards include such a stripe, and even when these stripes are present, they are difficult to read and require a purpose use reader. What is needed is an improved method of reading three-dimensional characters in a feeder system.
A further problem in the field is with the utilization of existing or legacy resources in a cost-effective manner. When new symbology techniques are implemented, while offering desirable improvements, they typically require the purchase of new readers to implement the new symbology. It can become exceedingly expensive to purchase a new reader for use with only minimal job runs using the new symbology, leaving the dilemma of whether to make the purchase or to wait. What is needed is a way to minimize the requirement to purchase new equipment each time a new symbology is utilized, and instead leverage existing legacy equipment to take advantage of any newly developed symbologies.
A further problem in the field is that prior art systems have generally required the use of multiple area-scanning cameras, one for each area targeted for an expected piece of information, such as an address or page number. These prior art methods have required the accurate positioning of a camera in the feeder, and accurate pre-printing of the information in a narrow area for each document in order to ensure its respective camera will image it. With the use of so many cameras, available good locations to mount them quickly become scarce, and the costs increase in proportion to the amount of required cameras. What is needed is a way to reduce the amount of cameras required.
A further problem in the field is that the target area for an area-scan camera is lit by a point source. Since the light needs to be close to the paper for adequate illumination, a ‘hot-spot’ is created on the image that is considerably lighter at the center and falls off towards the edges. There is no single threshold value that works across the entire image when reading scanned images. What is needed is a better way to read information through these difficult lighting conditions.
A further problem in the field is an inability to decode checks in a rapid manner in order to provide timely feedback to the feeder. The prior art approach has been to batch up all the images and decode them later, which proves to be too late for real-time control. What is needed is a way to rapidly decode checks in order to provide real-time feedback to the feeder.
For the foregoing reasons, there is a need for an improved feeder system and method.